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1,603 results for “stem cell differentiation”
Generation of beta-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids
<p>This repository contains single-cell RNA-sequencing data files (raw FASTQ files generated from Illumina HiSeq sequencing) related to the article entitled "Generation of beta-like cell subtypes from differentiated human induced pluripotent stem cells in 3D spheroids" by Lisa Morisseau et al. (2023) published in the Molecular Omics journal (DOI: 10.1039/d3mo00050h).</p> <p> </p>
Datasets for 'Label-free imaging of 3D pluripotent stem cell differentiation dynamics on chip'
<p>Here we publish the datasets associated with our publication ‘Label-free imaging of 3D pluripotent stem cell differentiation dynamics<br> on chip’. 3D cultures of human induced pluripotent stem cells (hiPSCs) were imaged while undergoing definitive endoderm (DE) differentiation.<br> Data were acquired either on the live 3D cultures at various time points during the 3 days DE differentiation, or after fixation and immunostaining, with the 3D cultures being fixed at regular 24 h intervals during differentiation, as to form a timeline. Images were recorded with a standard confocal microscope using a xy-resolution of 0.25 μm/px and a z-resolution of 1 μm/plane.</p>
RNA-seq - Definitive endoderm differentiation of human pluripotent stem cells in G1 phase
<p>Backup copy of the processed RNA-seq data at http://ngs.sanger.ac.uk/production/endoderm/</p>
Bulk RNA-seq dataset of human embryonic stem cells (hESCs) differentiation
<p>The dataset consists of 31 bulk samples obtained from human embryonic stem cells undergoing undirected differentiation. The samples were collected at 16 time points on days 0 and 7-21 of differentiation. The file contains the raw read counts.</p> <p>More details can be found in:</p> <p>SPIRAL: Significant Process InfeRence ALgorithm for single cell RNA-sequencing and spatial transcriptomics\<br> Hadas Biran, Tamar Hashimshony, Tamar Lahav, Or Efrat, Yael Mandel-Gutfreund, and Zohar Yakhini</p> <p> <a href="https://doi.org/10.1101/2022.05.24.493189">https://doi.org/10.1101/2022.05.24.493189</a></p>
Wolbachia endosymbionts manipulate the self-renewal and differentiation of germline stem cells to reinforce fertility of their fruit fly host
Open the record for dataset details and reuse information.
Data supporting 'Small molecule and cell contact-inducible systems for controlling expression and differentiation in stem cells'
<p>Data supporting Soliman et al. 2024. Manuscript describes data collection practices and experimental design.</p>
Rapid and Accurate Identification of Stem Cell Differentiation Stages via SERS and Convolutional Neural Networks
<p><a name="OLE_LINK2"></a><span>Monitoring the transition of cell states during induced pluripotent stem cell (iPSC) differentiation is crucial for clinical medicine and basic research. However, both identification category and prediction accuracy need further improvement. Here, we propose a method combining Surface-Enhanced Raman spectroscopy (SERS) with convolutional neural networks (CNN) to precisely identify and distinguish cell states during stem cell differentiation. First, mitochondria-targeted probes were synthesized by combining AuNRs and mitochondrial localization signal (MLS) peptides to obtain effective and stable SERS spectra signals at various stages of cell differentiation. Then, the SERS spectra served as input datasets, and their distinctive features were learned and distinguished by CNN. As a result, rapid and accurate identification of six different cell states, including the embryoid body (EB) stage, was successfully achieved throughout the stem cell differentiation process with an impressive prediction accuracy of 98.5%. Furthermore, the impact of different spectral feature peaks on the identification results was investigated, which provides a valuable reference for selecting appropriate spectral bands to identify cell states. This is also beneficial for shortening the spectral acquisition region to enhance spectral acquisition speed. These results suggest the potential for SERS-CNN models in quality monitoring of stem cells, advancing the practical applications of stem cells.</span></p>
Supplementary materials of Brain Extract of Subacute Traumatic Brain Injury Promotes Neuronal Differentiation of Human Neural Stem Cells Via Autophagy
<p>Figure S1: Characterization of hNSCs. In proliferate medium, the embryo derived hNSCs could form the neurospheres (A). Markers of NSCs (NES, SOX2, SOX1) were detected (B). The SOX2<sup>+</sup> cells accounted for >95% of all cells (C). Bar scale: 60μm;</p> <p>Figure S2: The proliferation of hNSCs in TBI brain extracts with different phases. Differentiated hNSCs could be labeled with EdU in TBI brain extracts with different phases (A). Ratio of EdU<sup>+</sup> cells was decreased with the progression of days post-injury (B). Bar scale: 75μm; ****: P<0.0001;</p> <p>Figure S3: The GO annotations and KEGG pathway analysis of different expressed pro-teins in acute brain extract and subacute brain extract;</p> <p>Table S1: The protein profiles of brain extract in acute phase and subacute phase after TBI.</p>
Sequence tracks of Ago2 Neural stem cells and differentiated neurons from single-cells- Related to Fig. 5
<p>Single neural stem cells were isolated from the Hippocampus of newborn mice generated from a hybrid cross. Some of these cells were differentiated In vitro and either the NSC or differentiated neurons were lysed and underwent a reverse transcription. The newly formed cDNA was used as a template to amplify expressed Ago2 transcript which was then sent off for Sanger sequencing. A SNP located within the exon was used to determine whether the transcript from that cell was generated from the maternal or paternal allele.</p>
Datasets accompanying "Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA-sequencing"
<p>Datasets include two seurat objects: one with all unfiltered cells and raw expression data (seu_unfiltered.rds) and one dataset with normalised expression and latest annotations (differentiation_object_latest.rds). Additionally, a single-cell object containing post-(py)SCENIC analysis is added (ipsc_scenic.h5ad).</p>
Data from: Drosophila medulla neuroblast termination via apoptosis, differentiation and gliogenic switch is scheduled by the depletion of the neuroepithelial stem cell pool
<p>The brain is consisted of diverse neurons arising from a limited number of neural stem cells. <em>Drosophila</em> neural stem cells called neuroblasts (NBs) produces specific neural lineages of various lineage sizes depending on their location in the brain. In the <em>Drosophila</em> visual processing centre - the optic lobes (OLs), medulla NBs derived from the neuroepithelium (NE) give rise to neurons and glia cells of the medulla cortex. The timing and the mechanisms responsible for the cessation of medulla NBs are so far not known. In this study, we show that the termination of medulla NBs during early pupal development is determined by the exhaustion of the NE stem cell pool. Hence, altering NE-NB transition during larval neurogenesis disrupts the timely termination of medulla NBs. Medulla NBs terminate neurogenesis via a combination of apoptosis, terminal symmetric division via Prospero, and a switch to gliogenesis via Glial Cell Missing (Gcm), however, these processes occur independently of each other. We also show that temporal progression of the medulla NBs is mostly not required for their termination. As the <em>Drosophila</em> OL shares a similar mode of division with mammalian neurogenesis, understanding when and how these progenitors cease proliferation during development can have important implications for mammalian brain size determination and regulation of its overall function.</p>
Efficient improvement of the proliferation, differentiation, and anti-arthritic capacity of mesenchymal stem cells by simply culturing on the immobilized FGF2 derived peptide, 44-ERGVVSIKGV-53
<p>All data needed to evaluate the results presented in the paper: Soo Bin Lee, Ahmed Abdal Dayem, Sebastian Kmiecik, Kyung Min Lim, Dong Sik Seo, Hyeong-Taek Kim, Polash Kumar Biswas, Minjae Do, Deok-Ho Kim, Ssang-Goo Cho, Efficient improvement of the proliferation, differentiation, and anti-arthritic capacity of mesenchymal stem cells by simply culturing on the immobilized FGF2 derived peptide, 44-ERGVVSIKGV-53,<br>Journal of Advanced Research, Volume 62,<br>2024,<br>Pages 119-141,<br>ISSN 2090-1232,<br>https://doi.org/10.1016/j.jare.2023.09.041.</p>
Lattice kinetic Monte Carlo model to simulate RNA polymerase II clusters during stem cell differentiation
<p>This data set includes Python scripts (numerical simulation and analysis) and already generated simulation data for RNA polymerase II clusters during stem cell differentiation. It includes the whole data to recreate panels.</p>
Microscopy-based assessment of RNA polymerase II clusters during differentiation of cultured mouse embryonic stem cells
<p>This repository contains the data and MatLab analysis scripts of the analysis of RNA polymerase II clusters over the course of differentiation of cultured mouse embryonic stem cells (mESCs). The cells were induced towards differentiation by either withdrawal of lineage-inhibiting factors (-LIF) or by RHB treatment. Both treatments were carried out in duplicate in independent experiments. Time course data were obtained by collection of cells at 3, 6, 12, 24, and 48 hours following the beginning of induction. Control data from unindexed cells were obtained at 24 and 48 hours. Cells were cultured, treated, collected, and fixed at University Medical Center Göttingen by Yomna Gohar, Priya Kumar, and Carmelo Ferrai. Fixed cells were fluorescently labeled and microscopy images were recorded and analyzed at Karlsruhe Institute of Technology by Lennart Hilbert. </p> <p>To analyse date data, the raw image data are first extracted into MatLab-native files using the <a href="https://zenodo.org/api/files/2f2192f4-a05c-4969-ba0a-4f235b837709/MultiPosition_extraction_nd2.m">MultiPosition_extraction_nd2.m</a> script. The actual analysis is then carried out using the <a href="https://zenodo.org/api/files/2f2192f4-a05c-4969-ba0a-4f235b837709/ClusterAnalysis.m">ClusterAnalysis.m</a> script. Example microscopy images were produced using the <a href="https://zenodo.org/api/files/2f2192f4-a05c-4969-ba0a-4f235b837709/ExampleImages.m">ExampleImages.m</a> script. The extracted data can be reviewed using the <a href="https://zenodo.org/api/files/2f2192f4-a05c-4969-ba0a-4f235b837709/ReviewExtractedStacks.m">ReviewExtractedStacks.m</a> script.</p> <p>This is the main repository, containing the image analysis scripts alongside the links to the raw image data used in the analysis. The raw data are too large to be stored within this single repository, and therefore can be found at the following additional addresses.</p> <p>Differentiation by withdrawal of lineage-inhibiting factors (-LIF): <a href="https://doi.org/10.5281/zenodo.8013281">10.5281/zenodo.8013281</a></p> <p>Differentiation with addition of RHB for neuronal fate induction (RHB): <a href="https://doi.org/10.5281/zenodo.8013307">10.5281/zenodo.8013307</a></p>
Data from: Drosophila medulla neuroblast termination via apoptosis, differentiation and gliogenic switch is scheduled by the depletion of the neuroepithelial stem cell pool
Open the record for dataset details and reuse information.
Differentiation of parathyroid hormone expressing cells from human pluripotent stem cells
Abstract Differentiation of pluripotent stem cells into functional parathyroid-like cells would accelerate development of important therapeutic options for subjects with parathyroid-related disorders, from the design and screening of novel pharmaceutical agents to the development of durable cellular therapies. We have established a highly reproducible directed differentiation approach leading to parathyroid hormone (PTH) expressing cells from human embryonic stem cells (hESC) and induced pluripotent stem cells (iPSC). We accomplished this through the comparison of multiple different basal media, the inclusion of the CDK inhibitor PD0332991 in both definitive endoderm (DE) and anterior foregut endoderm (AFE) stages, and a 2-stage pharyngeal endoderm (PE) series. This is the first protocol to reproducibly establish PTH expressing-cells from human pluripotent stem cells and represents a first step towards the development of functional parathyroid cells with broad applicability for medicinal and scientific investigation.
Endocannabinoid signalling in stem cells and cerebral organoids drives differentiation to deep layer projection neurons via CB1 receptors
<p>The endocannabinoid (eCB) system, <i>via</i> cannabinoid CB<sub>1</sub> receptor, regulates neurodevelopment by controlling neural progenitor proliferation and neurogenesis. CB<sub>1</sub> receptor signalling <i>in vivo</i> drives corticofugal deep layer projection neuron development through the regulation of <span>BCL11B </span>and <span>Satb2</span> transcription factors. Here, we investigated the role of eCB signalling in mouse pluripotent embryonic stem cell-derived neuronal differentiation. Characterization of the eCB system revealed increased expression of eCB-metabolizing enzymes, eCB ligands and CB<sub>1</sub> receptors along neuronal differentiation. CB<sub>1</sub> receptor knockdown inhibited neuronal differentiation of deep layer neurons and increased upper layer neuron generation, and this phenotype was rescued by CB<sub>1</sub> re-expression. Pharmacological regulation with CB<sub>1</sub> receptor agonists or elevation of eCB tone with a monoacylglycerol lipase inhibitor promoted neuronal differentiation of deep layer neurons at the expense of upper layer neurons. Patch-clamp analyses revealed that enhancing cannabinoid signalling facilitated neuronal differentiation and functionality. Noteworthy, incubation with CB<sub>1</sub> receptor agonists during human iPSC-derived cerebral organoid formation also promoted the expansion of BCL11B<sup>+</sup> neurons. These findings unveil a cell-autonomous role of eCB signalling that, <i>via</i> CB<sub>1</sub> receptor, promotes mouse and human deep layer cortical neuron development.</p>
H3K4me1 marks DNA regions hypomethylated during aging in human stem and differentiated cells
<p>In differentiated cells, aging is associated with hypermethylation of DNA regions enriched in repressive histone post-translational modifications. However, the chromatin marks associated with changes in DNA methylation in adult stem cells during lifetime are still largely unknown. Here, DNA methylation profiling of mesenchymal stem cells (MSCs) obtained from individuals aged 2 to 92 yr identified 18,735 hypermethylated and 45,407 hypomethylated CpG sites associated with aging. As in differentiated cells, hypermethylated sequences were enriched in chromatin repressive marks. Most importantly, hypomethylated CpG sites were strongly enriched in the active chromatin mark H3K4me1 in stem and differentiated cells, suggesting this is a cell type-independent chromatin signature of DNA hypomethylation during aging. Analysis of scedasticity showed that interindividual variability of DNA methylation increased during aging in MSCs and differentiated cells, providing a new avenue for the identification of DNA methylation changes over time. DNA methylation profiling of genetically identical individuals showed that both the tendency of DNA methylation changes and scedasticity depended on nongenetic as well as genetic factors. Our results indicate that the dynamics of DNA methylation during aging depend on a complex mixture of factors that include the DNA sequence, cell type, and chromatin context involved and that, depending on the locus, the changes can be modulated by genetic and/or external factors.</p>
Dataset for puplication: Machine Learning in Automated Monitoring of Metabolic Changes Accompanying the Differentiation of Adipose Tissue-Derived Human Mesenchymal Stem cells employing 1H-1H TOCSY NMR
<p>Data set used in the publication: <strong>Machine Learning in Automated Monitoring of Metabolic Changes Accompanying the Differentiation of Adipose Tissue-Derived Human Mesenchymal Stem cells employing <sup>1</sup>H-<sup>1</sup>H TOCSY NMR. </strong></p> <p>Abstract: In this work, the dynamic evolution of adipose tissue-derived human MSCs (AT-derived hMSCs) after fourteen days of cultivation, adiobocytes and osteocytes differentiation has been inspected based on 2D NMR TOCSY using machine learning techniques. Multi-class classification in addition to novelty detection of metabolites was established based on the profile of a control hMSCs sample at four days cultivation and successively detect the absence and the abundance of metabolites in differentiated MSCs following a set of <sup>1</sup>H-<sup>1</sup>H TOCSY profiles. The uploaded files are:</p> <p>File: metabolites_names.xlsx contain the names of the used metabolites.</p> <p>File: metabolites.xlsx</p> <p> column 1: metabolite abbreviation</p> <p>column 2: 2D NMR TOCSY horizontal and vertical frequencies of metabolites in the control group at 4 days cultivation (Ct d4)</p> <p>column 3: 2D NMR TOCSY horizontal and vertical frequencies of metabolites found after 14 days of cultivation (Ct d14)</p> <p>column 4: 2D NMR TOCSY horizontal and vertical frequencies of metabolites found after 14 days of differentiation into adipocytes (AT d14)</p> <p>column 5: 2D NMR TOCSY horizontal and vertical frequencies of metabolites found after14 days of differentiation into osteocytes (OS d14)</p> <p>column 6: 2D NMR TOCSY horizontal and vertical standard frequencies of all metabolites measured at broadband high resolution 600.13 MHz NMR</p>
ATAC-seq - Definitive endoderm differentiation of human pluripotent stem cells in G1 phase
<p>Backup copy of the processed ATAC-seq data at http://ngs.sanger.ac.uk/production/endoderm/</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.